accordant-state

A guide to designing state models in Accordant, a framework for describing how systems change during operations. State is the information needed to predict what an operation should return.

In plain words
What is it for?
Use it when defining Accordant state, including the data operations need and the automatically generated cloning, comparison, and hashing behavior.
Why use it?
It helps keep models small and behavior-focused instead of mixing in database details or other implementation information.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/microsoft/accordant/state
Any agent
npx skills add microsoft/accordant --skill state
Clone the repo
git clone --depth 1 https://github.com/microsoft/accordant

Made for: Claude Code, Codex.

Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,268 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00024 $0.01268
Opus 5 $0.00012 $0.00634
Sonnet 5 $0.00005 $0.00254
Haiku 4.5 $0.00002 $0.00127

Measured 2d ago against content hash 051cb1258279, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

accordant-state scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agent/skills/state/SKILL.md · 193 lines

How it starts

The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Designing State in Accordant

State is what an external observer needs to know to predict what an operation should return. Keep it minimal — only track what's necessary to define correct behavior.

The [State] Attribute

Use [State] on a partial class to get automatic cloning, equality, and hashing:

[State]
public partial class BankState
{
    public Dictionary<string, decimal> Accounts { get; set; } = new();
}

The source generator handles:

  • Deep cloning for immutable state transitions
  • Equality comparison for state deduplication
  • Hashing for state graph exploration

State Design Principles

Keep It Minimal

Ask: "Does any operation need this to determine its response?" If no, leave it out.

// ❌ Too detailed - includes implementation concerns
[State]
public partial class BadState
{
    public Dictionary<string, AccountEntity> Accounts { get; set; }  // EF entities
    public DateTime LastModified { get; set; }  // Not needed for behavior
    public string ConnectionString { get; set; }  // Implementation detail
}

// ✅ Just what operations need
[State]
public partial class GoodState
{
    public Dictionary<string, decimal> Accounts { get; set; } = new();  // Just balances
}

Nested State Classes

For complex domains, nest state classes:

[State]
public partial class AppState
{
    public Dictionary<string, UserState> Users { get; set; } = new();
}

[State]
public partial class UserState
{
    public string Name { get; set; } = string.Empty;
    public Dictionary<string, TodoState> Todos { get; set; } = new();
}

[State]
public partial class TodoState
{
    public string Title { get; set; } = string.Empty;
    public bool Completed { get; set; } = false;
}

State Transitions

Operations return expected outcomes that describe both the response and the next state.

No State Change: .SameState()

For errors or read-only operations:

// Error - doesn't modify state
if (!state.Accounts.ContainsKey(accountId))
    return Expect.That<ApiResult<decimal>>(r => r.IsNotFound).SameState();

// Read-only operation
return Expect.That<ApiResult<decimal>>(r => r.IsSuccess && r.Data == balance).SameState();

Read the full file on GitHub · 193 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 193 lines · 24 tokens per session scan A 051cb1258279

Subscribe to this mod's changes

accordant-state is a skill published in the GitHub repository microsoft/accordant (58 stars, last pushed 14d ago), licensed MIT. It adds 24 tokens to every session and 1,268 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.